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Returning Users
from Activation
Metrics type
Result
Units of measure
Quantitative
Direction
More - better
Check frequency
Daily
Description
The number of users who have initiated at least one previous session, regardless of whether or not the previous sessions were engaged sessions.
Why it is important
"Returning Users" metric helps businesses understand the effectiveness of their retention strategies and the overall appeal of their platform to users who have previously interacted with it.
By analyzing Returning Users, businesses can make data-driven decisions to enhance user experience, tailor marketing efforts, and foster long-term customer relationships.
By analyzing Returning Users, businesses can make data-driven decisions to enhance user experience, tailor marketing efforts, and foster long-term customer relationships.
Formula
Number of Returning Users
Calculation example
At the start of January, the e-commerce store has 10,000 users with past sessions.
Throughout January, 2,000 new users sign up.
During January, 3,000 users who had initiated sessions in the past return for another session.
The number of Returning Users for January would be 3,000, as these are users who had initiated at least one session in the past and returned during the month.
Throughout January, 2,000 new users sign up.
During January, 3,000 users who had initiated sessions in the past return for another session.
The number of Returning Users for January would be 3,000, as these are users who had initiated at least one session in the past and returned during the month.
Affected metrics
Total Users
Registrations
Registrations
Affecting metrics
Users Churn Rate
Connecting metrics
Inter-Visit Time Distribution
Users Loyalty Rate
Users Loyalty Rate
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Suggested slices for dashboards
by Frequency
by Traffic Source
by Time-of-Day and Day-of-Week
by Product Category
by Device Type
by Geo
by Referral Source
by Loyalty Program Level
by Seasonal or Event-Based Trends
by Traffic Source
by Time-of-Day and Day-of-Week
by Product Category
by Device Type
by Geo
by Referral Source
by Loyalty Program Level
by Seasonal or Event-Based Trends
The revenue impact pathway
Available in JetMetrics Lite only
Questions to be Answered
1. How does the number of Returning Users correlate with changes in user engagement strategies or major app updates, and what insights can be gained for retaining and re-engaging users over time?
2. Are there specific app features or events that consistently lead to higher Returning Users, and how can these be emphasized for better user retention and satisfaction?
3. Can you identify any correlation between the timing and frequency of push notifications or in-app messages and changes in the number of Returning Users?
4. How does the number of Returning Users differ between users who have completed the activation process and those who haven't?
5. What impact do limited-time promotions or exclusive offers have on the number of Returning Users, and how can these promotions be optimized for increased user retention and re-engagement?
6. How does the geographic location of users influence the number of Returning Users, and are there opportunities for localized optimization of user retention strategies?
7. What is the correlation between the number of Returning Users and user satisfaction scores, and how can improvements in user satisfaction contribute to a higher number of returning users?
2. Are there specific app features or events that consistently lead to higher Returning Users, and how can these be emphasized for better user retention and satisfaction?
3. Can you identify any correlation between the timing and frequency of push notifications or in-app messages and changes in the number of Returning Users?
4. How does the number of Returning Users differ between users who have completed the activation process and those who haven't?
5. What impact do limited-time promotions or exclusive offers have on the number of Returning Users, and how can these promotions be optimized for increased user retention and re-engagement?
6. How does the geographic location of users influence the number of Returning Users, and are there opportunities for localized optimization of user retention strategies?
7. What is the correlation between the number of Returning Users and user satisfaction scores, and how can improvements in user satisfaction contribute to a higher number of returning users?
Possible causes of worsening
n/a
Tactics to improve this metric
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